Examining the validity of the drivers of COVID-19 vaccination acceptance scale using Rasch analysis

Chia Wei Fan, Jung Sheng Chen, Frimpong Manso Addo, Emma Sethina Adjaottor, Gifty Boakye Amankwaah, Cheng Fang Yen, Daniel Kwasi Ahorsu, Chung Ying Lin

研究成果: Article同行評審

28 引文 斯高帕斯(Scopus)

摘要

Background: To well control the pandemic of COVID-19, herd immunity should be achieved. However, people, especially those with better physical conditions (e.g., young adults), may not accept COVID-19 vaccines. Understanding university students’ willingness or reluctance to uptake COVID-19 vaccination is important. Aim: This study aimed to examine the psychometric properties of the DrVac-COVID19S, an instrument that helps assess motivations/drivers of COVID-19 vaccination uptake among university students. Research Design and Methods: Using convenience sampling and cross-sectional design, university students (930 from Taiwan [38.0% males] and 1,244 from Ghana [63.3% males]) completed the DrVac-COVID19S using an online survey (Taiwanese students) or paper-and-pen method (Ghanaian students). Rasch analysis was used to examine the psychometric properties of the DrVac-COVID19S. Results: All 12 items in the DrVac-COVID19S had a satisfactory fit in the Rasch models (infit MnSq = 0.74 to 1.49; outfit MnSq = 0.72 to 1.42). Moreover, the seven-point Likert scale used in the DrVac-COVID19S demonstrated monotonically increasing in their difficulties, which indicated the ordered category. Additionally, no differential item functioning was displayed in the DrVacCOVID-19S across Taiwanese and Ghanaian students. Conclusions: The DrVacCOVID-19S has good psychometric features to help healthcare providers assess individuals’ (especially university students) motivations or drivers to get the COVID-19 vaccination.

原文English
頁(從 - 到)253-260
頁數8
期刊Expert Review of Vaccines
21
發行號2
DOIs
出版狀態Published - 2022

All Science Journal Classification (ASJC) codes

  • 免疫學
  • 分子醫學
  • 藥理
  • 藥物發現

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